RedisIt is based onMultiplexingI/O model that allows Redis to efficiently handle large number of client connections while maintaining highperformanceand low latency. Below is a detailed analysis of the Redis multiplexed I/O model.
1. What is multiplexing I/OModel？
The multiplexed I/O model refers to monitoring multiple file descriptors (or sockets) in a thread. When a file descriptor is ready for I/O operations (such as read or write), the operating system notifies the application so that the application can perform corresponding I/O operations on the file descriptor without having to create a thread or process for each connection. The core of the multiplexed I/O model is the ability to handle multiple I/O operations through a single thread.
2. Redis's multiplexed I/O implementation
Redis's multiplexing I/O model mainly relies on the I/O multiplexing mechanism provided by the operating system, and different operating systems provide different multiplexing mechanisms:
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Linux:
epoll -
macOS:
kqueue -
Windows:
IOCP -
Other Unix systems:
selectorpoll
When Redis is initialized, it will select the appropriate I/O multiplexing method according to the operating system (usuallyepollorkqueue) and use this mechanism to process allClientConnection and I/O events.
3. Redis event handling mechanism
Redis uses an event-driven programming pattern to handle I/O operations through an event loop. The event loop is mainly composed of the followingComponentscomposition:
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File Event Processor: The file event processor in Redis is based on the I/O multiplexing mechanism, which is responsible for listening to the readable and writable states of multiple file descriptors and mapping these states into corresponding events.
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Time Event Processor: The time event processor is used to handle tasks that need to be executed regularly, such as Redis's regular tasks or delayed tasks.
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Event dispatcher: The event dispatcher is responsible for obtaining events from the file event processor and the time event processor, and then calling the corresponding event processor for processing.
4. Redis file event processing process
The workflow of the Redis file event processor is as follows:
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Register Events: When a new client connects to Redis, Redis registers the file descriptor for this connection to the file event processor and specifies the type of event to be listened to (such as read or write).
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Event loop: Redis enters the event loop and calls the I/O multiplexing function (such as
epoll_waitorkqueue) Blocking waiting for events on file descriptors. -
Event trigger: When an event on a file descriptor (such as a read event) is ready, the multiplex function returns one or more prepared file descriptors.
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Event handling: Redis calls the corresponding event handling function according to the event type. For example, for read events, Redis reads data from the client and processes it.
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Continue the loop: After processing the event, Redis continues to enter the event loop and waits for a new event to occur.
5. Advantages of multiplexing models
- Efficiency: Processing multiple connections through a single thread avoids switching overhead for threads or processes.
- Scalability: The I/O multiplexing mechanism allows Redis to handle thousands of client connections simultaneously.
- Simplicity: Redis's code implementation keeps simple and clear, and the entire event loop is executed in a single thread, avoiding the complexity of multi-threaded programming.
6. Single-threaded features of Redis
Although Redis is single-threaded, this does not mean it is performing poorly. Thanks to I/O multiplexing and efficient data structures, Redis can efficiently handle large quantities in a single threadconcurrentconnect. In addition, Redis's single-threaded feature simplifies the programming model and avoids common problems in multi-threaded programming such as lock competition and deadlock.
Summarize
Redis's multiplexing-based I/O model allows it to maintain high performance and low latency in high concurrency scenarios. Through I/O multiplexing mechanism, Redis can efficiently handle large number of client requests in a single thread, which is one of the key reasons why Redis can become a high-performance database.